Search

Digital fountain code is a kind of error correction code with good coding and decoding performance, adaptive channel environment, and minimizing information feedback. Digital fountain code have been widely used in deep space communication, network communication and other fields. Luby Transform(LT) code is the first practical solution for digital fountain code, and it is also the basis for the improvement of other types of fountain code. However, the traditional LT code coding and decoding methods always have problems such as decoding overhead and high probability of decoding failure, which need to be further studied and solved.Aiming at the problem that the traditional uniform selection coding algorithm of digital fountain code reduces the performance of the coding algorithm due to incomplete coverage of the source packets, this paper studies an improved non-uniform selection coding algorithm, by increasing the degree of some nodes, and preferentially selecting unparticipated coded source packets, effectively improves coverage of source packets. Simulation results show that the performance of the improved coding algorithm is significantly improved compared with the traditional coding algorithm.

For the complete coverage path planning of multi-AUVs (autonomous underwater vehicles), a method of cooperative complete coverage path planning for multi-AUVs based on GBNN algorithm is proposed in this paper, where all AUVs share the common working environment information, and each AUV treats other AUVs as moving obstacles. Firstly, a grid map is constructed by discretizing the underwater workspace. Secondly, the corresponding dynamic neural networks are built on the grid map, and there are N neural networks for N AUVs, respectively. Finally, each AUV plans its reasonable coverage path according to its own neural activity through GBNN strategy, until work together to cover the entire workspace. The simulation results show that multi-AUVs can not only cooperatively accomplish the common coverage tasks without any mutual collision and overlapped coverage, but also automatically avoid obstacles and escape from deadlocks, and effectively improve work efficiency of each single AUV, reduce complete coverage time and save AUVs' power.

Facial expression classification is a very challenging problem in machine perception, which plays an important role in many visual applications. In this paper, we use a machine-learning-based framework to address this problem. We firstly apply K-SVD to learn sparse representations of the face images in the training set in an unsupervised manner for image modeling. After that we train a SVM classifier in a supervised manner on those representations, and then the obtained classifier would be used for facial expression classification. Our experimental results show that the learned dictionaries by K-SVD can not only capture meaningful features from the faces for facial expression modeling, but also help to boost the performance of the subsequent SVM classifier in terms of classification accuracies and speeds.

Under the condition of random communication delays, this paper deals with the problem of fault detection for networked switched systems with arbitrary switching laws. The delay of data packets include the measured output and the switched signal and the delays satisfy the Bernoulli random binary distribution. By using multiple Lyapunov function, a general observer-based fault detection filter is designed and applied as the residual generation system. Then the design of fault detection filter is formulated as H∞ filtering problem in terms of H∞ theory. Sufficient condition for the existence of the filter is established by means of linear matrix inequalities (LMI) at last. A numerical example shows the validity of the proposed method.

Ultra Wide Bandwidth (UWB) system based on Parallel Combinatory Spread Spectrum (PCSS-UWB), combined low interception Probability of UWB system with high data transmission efficiency of Parallel Combinatory Spread Spectrum System, can fulfill the needs of modern communication system in efficiency and security. Through the simulation, it shows that PCSS-UWB system has a better bit error rate (BER) Performance under the additive white Gaussian noise (AWGN) background. Furthermore, the BER performance of PCSS-UWB system by using different pseudo-noise sequences is analyzed and the result proves the BER performance is related to the period of pseudo-noise sequences, but not the categories of pseudo-noise sequence.

A new ultra wideband (UWB) communication system based on parallel combinatory spread spectrum (PCSS) is proposed in this paper. The proposed system have the advantages both of PCSS system and UWB system, such as the high efficiency of information transmission and excellent secret property. Thus, the proposed system can meet the needs of efficiency and security as the same time in the modern communication system. The simulation model is provided and the performance is analyzed. The simulation results indicate that the UWB system based on PCSS has a better bit error rate (BER) performance.